{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:X2C5VF6V2D4UMYAQGCAOC4VPV3","short_pith_number":"pith:X2C5VF6V","canonical_record":{"source":{"id":"1810.02010","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-04T00:25:02Z","cross_cats_sorted":[],"title_canon_sha256":"215a1169b61711b42f04eeff983f13e8af283386bb7323f84feb9f95227a6d5a","abstract_canon_sha256":"7823193ba1ed29135ef488bfc10cdcb6e3ae9176bf1f9c20e7ecef71b9e6736f"},"schema_version":"1.0"},"canonical_sha256":"be85da97d5d0f94660103080e172afaeccbe99d0b27e6c6d03595f686e617c5c","source":{"kind":"arxiv","id":"1810.02010","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.02010","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"arxiv_version","alias_value":"1810.02010v1","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.02010","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"pith_short_12","alias_value":"X2C5VF6V2D4U","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"X2C5VF6V2D4UMYAQ","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"X2C5VF6V","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:X2C5VF6V2D4UMYAQGCAOC4VPV3","target":"record","payload":{"canonical_record":{"source":{"id":"1810.02010","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-04T00:25:02Z","cross_cats_sorted":[],"title_canon_sha256":"215a1169b61711b42f04eeff983f13e8af283386bb7323f84feb9f95227a6d5a","abstract_canon_sha256":"7823193ba1ed29135ef488bfc10cdcb6e3ae9176bf1f9c20e7ecef71b9e6736f"},"schema_version":"1.0"},"canonical_sha256":"be85da97d5d0f94660103080e172afaeccbe99d0b27e6c6d03595f686e617c5c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:06.574113Z","signature_b64":"AMwship3Pv5hGNJe1+UX51c8annRrYsY70/K3uIFlBrUU/vdEtazowlyUTbsmnpHzBfMtIzwXp1wEdJ7Yu55CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"be85da97d5d0f94660103080e172afaeccbe99d0b27e6c6d03595f686e617c5c","last_reissued_at":"2026-05-18T00:04:06.573432Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:06.573432Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.02010","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:04:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xTZKhuU93SK7mShITN/roh+dMhUrhTW1WUey4XBTNSIOK0aYFZLD/MbL7aG/fTr3OMfaDOwYcCckE3BuSfN+Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T23:24:25.014614Z"},"content_sha256":"08c36eeb7e3de1e7269bedef627643daf89f54978d4aaa690760582d0958108d","schema_version":"1.0","event_id":"sha256:08c36eeb7e3de1e7269bedef627643daf89f54978d4aaa690760582d0958108d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:X2C5VF6V2D4UMYAQGCAOC4VPV3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Domain Specific Approximation for Object Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chia-Lin Yu, Hasan Genc, Matthew Halpern, Shiao-Li Tsao, Ting-Wu Chin, Vijay Janapa Reddi","submitted_at":"2018-10-04T00:25:02Z","abstract_excerpt":"There is growing interest in object detection in advanced driver assistance systems and autonomous robots and vehicles. To enable such innovative systems, we need faster object detection. In this work, we investigate the trade-off between accuracy and speed with domain-specific approximations, i.e. category-aware image size scaling and proposals scaling, for two state-of-the-art deep learning-based object detection meta-architectures. We study the effectiveness of applying approximation both statically and dynamically to understand the potential and the applicability of them. By conducting exp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.02010","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:04:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/3qGbsmNb2FwTjsCkNTltp8qekmOeN0NE67kie+Smk0EF3NDovtkeH+xHgJAwYnK/pnnxay/rrW69RqNRIeuCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T23:24:25.015103Z"},"content_sha256":"1a51af215115cdc7bcb358b621ccbfed32f0bc86c1b7a6fd3a1137a3aaf64f07","schema_version":"1.0","event_id":"sha256:1a51af215115cdc7bcb358b621ccbfed32f0bc86c1b7a6fd3a1137a3aaf64f07"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X2C5VF6V2D4UMYAQGCAOC4VPV3/bundle.json","state_url":"https://pith.science/pith/X2C5VF6V2D4UMYAQGCAOC4VPV3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X2C5VF6V2D4UMYAQGCAOC4VPV3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-27T23:24:25Z","links":{"resolver":"https://pith.science/pith/X2C5VF6V2D4UMYAQGCAOC4VPV3","bundle":"https://pith.science/pith/X2C5VF6V2D4UMYAQGCAOC4VPV3/bundle.json","state":"https://pith.science/pith/X2C5VF6V2D4UMYAQGCAOC4VPV3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X2C5VF6V2D4UMYAQGCAOC4VPV3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:X2C5VF6V2D4UMYAQGCAOC4VPV3","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"7823193ba1ed29135ef488bfc10cdcb6e3ae9176bf1f9c20e7ecef71b9e6736f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-04T00:25:02Z","title_canon_sha256":"215a1169b61711b42f04eeff983f13e8af283386bb7323f84feb9f95227a6d5a"},"schema_version":"1.0","source":{"id":"1810.02010","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.02010","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"arxiv_version","alias_value":"1810.02010v1","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.02010","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"pith_short_12","alias_value":"X2C5VF6V2D4U","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"X2C5VF6V2D4UMYAQ","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"X2C5VF6V","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:1a51af215115cdc7bcb358b621ccbfed32f0bc86c1b7a6fd3a1137a3aaf64f07","target":"graph","created_at":"2026-05-18T00:04:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"There is growing interest in object detection in advanced driver assistance systems and autonomous robots and vehicles. To enable such innovative systems, we need faster object detection. In this work, we investigate the trade-off between accuracy and speed with domain-specific approximations, i.e. category-aware image size scaling and proposals scaling, for two state-of-the-art deep learning-based object detection meta-architectures. We study the effectiveness of applying approximation both statically and dynamically to understand the potential and the applicability of them. By conducting exp","authors_text":"Chia-Lin Yu, Hasan Genc, Matthew Halpern, Shiao-Li Tsao, Ting-Wu Chin, Vijay Janapa Reddi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-04T00:25:02Z","title":"Domain Specific Approximation for Object Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.02010","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:08c36eeb7e3de1e7269bedef627643daf89f54978d4aaa690760582d0958108d","target":"record","created_at":"2026-05-18T00:04:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"7823193ba1ed29135ef488bfc10cdcb6e3ae9176bf1f9c20e7ecef71b9e6736f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-04T00:25:02Z","title_canon_sha256":"215a1169b61711b42f04eeff983f13e8af283386bb7323f84feb9f95227a6d5a"},"schema_version":"1.0","source":{"id":"1810.02010","kind":"arxiv","version":1}},"canonical_sha256":"be85da97d5d0f94660103080e172afaeccbe99d0b27e6c6d03595f686e617c5c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"be85da97d5d0f94660103080e172afaeccbe99d0b27e6c6d03595f686e617c5c","first_computed_at":"2026-05-18T00:04:06.573432Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:04:06.573432Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AMwship3Pv5hGNJe1+UX51c8annRrYsY70/K3uIFlBrUU/vdEtazowlyUTbsmnpHzBfMtIzwXp1wEdJ7Yu55CA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:04:06.574113Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.02010","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:08c36eeb7e3de1e7269bedef627643daf89f54978d4aaa690760582d0958108d","sha256:1a51af215115cdc7bcb358b621ccbfed32f0bc86c1b7a6fd3a1137a3aaf64f07"],"state_sha256":"1bdd951825820a90b617e5de1bb7fb9022d25f793c2194211099aaf4ff59cf56"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DqWeSHOOoFDEUJ2ClogQmiIIeALX4m9lyd4GdNNSoBDD8f1dmWZlYuJVo1/U1lTuGoVKh8KxfoeQ+ZPghwiWCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T23:24:25.018163Z","bundle_sha256":"977a566a366e137e58534c21947ddf262add767e7c52dbad50e75f099106f788"}}